• DocumentCode
    2515300
  • Title

    Diagnosis of transformer winding deformation on the basis of artificial neural network

  • Author

    Zhijian, Jin ; Jingtao, Li ; Zishu, Zhu

  • Author_Institution
    Shanghai Jiaotong Univ., China
  • Volume
    1
  • fYear
    2000
  • fDate
    2000
  • Firstpage
    173
  • Abstract
    It needs much experience to determine the deformation of the transformer winding with the FRA method. This paper introduces the BP neural network and discusses some calculation improvements in order to apply it to the practical engineering problem. As a result it can recognize the deformation of the transformer winding automatically and effectively through studying various practical examples
  • Keywords
    automatic testing; backpropagation; feedforward neural nets; power engineering computing; power transformer testing; transformer windings; BP neural network; FRA method; artificial neural network; backpropagation; diagnosis; feedforward neural network; transformer winding deformation; Artificial neural networks; Backpropagation algorithms; Feedforward neural networks; Frequency; Neural networks; Neurons; Power transformers; Stress; US Department of Transportation; Windings;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Properties and Applications of Dielectric Materials, 2000. Proceedings of the 6th International Conference on
  • Conference_Location
    Xi´an
  • Print_ISBN
    0-7803-5459-1
  • Type

    conf

  • DOI
    10.1109/ICPADM.2000.875658
  • Filename
    875658